Working with ever-changing CDISC standards

When Jack Shostak and I first started thinking about writing a SAS book on implementing CDISC (Clinical Data Interchange Standards Consortium) standards, we held one truth to be self-evident: that at least some parts of the book would be outdated before it was even published. Thanks to some lucky timing and the ability to make some minor tweaks just prior to publishing, the extent of the “outdated-ness” with our first edition of Implementing CDISC Using SAS: An End-to-End Guide, was fairly limited…for a few weeks at least.

Shortly after publishing, the final version 2.0 of the Define-XML specification came out and we knew there was some work to do in the future. So, after a bit of a writing break, we rolled up our sleeves again and began updating our %make_define macro and the associated metadata spreadsheets for the second edition of our book. Quite a few other changes were also in the works!

That edition came out in November of 2016. However, CDISC standards didn’t stop for us. True to form, even before publishing, we realized that we weren’t implementing NCI codes, aka “C-codes”, in our metadata-controlled terminology.

This was painfully obvious thanks to a check that started coming up in the Pinnacle 21 reports: “Missing NCI Code for Term in Codelist”. Some users shared this feedback with us, and we took action (thank you, users!).

So with some motivation from Jack, I started working on implementing C-codes. But I wanted it to be slick. The codes are all on the NCI website spreadsheets, so why should we expect users to enter them all into their study-specific metadata spreadsheets, right? Why not just read those spreadsheets, also available in XML format, and automatically merge the C-codes into the study-specific data? Well, I can tell you why it wasn’t that easy.

About Author

Regulatory agencies, and both small and large pharmaceutical and biotechnology companies. He was first introduced to CDISC while working as a statistical reviewer at the Center for Drug Evaluation and Research in the U.S. Food and Drug Administration. There he served as the technical lead for the SDTM/ADaM Pilot Project FDA review team and invented an early version of the MAED Service, an adverse event review tool that made use of data standards and is currently in production at the FDA. Since leaving the FDA, Holland continues to be active in the CDISC community, particularly with the ADaM team. He received an MS in statistics from the University of Virginia, a BS in statistics from Virginia Tech, and is an Accredited Professional Statistician™ by the American Statistical Association.